Long-Term Energy Modeling and Forecasting. The energy sector uses long-term (1 to 20 years) energy forecasting to plan for and develop electricity generation to meet long-term demand. Long-term forecasting includes everything from planning by utilities for expanding production over a 1- to 10-year period to long-term scenario analysis useful for setting regional and national energy policy. Long-term energy forecasting and scenario models use inputs such as historical and projected loads, average meteorological and climate data, available energy sources, resource availability, environmental impacts, and economic data. In other cases, individual models are linked or reconciled in an integrated assessment model that brings together a broader set of areas, methods, styles of study, or degrees of certainty, than would typically characterize a study of the same issue within the bounds of a single research discipline. Potentially Relevant NASA Resources ▪ Meteorology data ▪ Climate models ▪ Renewable energy resources, such as solar radiation and wind sources, and expected changes to those resources due to long-term climate changes Current Status/Relevant Issues With climate change uncertainty and rapidly growing energy needs, the need for better and relevant data for long-term energy models is significant. A variety of government, non-profit organizations, and private companies conduct long-term energy forecasting to meet their own or support others’ specific decision-making needs. For example, the Energy Information Administration (EIA), an independent agency within DOE, designed and implements the National Energy Modeling System (NEMS).93 This computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2025 is used by EIA to project the energy, economic, environmental, and security impacts on the U.S. of alternative energy policies and different assumptions about energy markets. The model relies on input data such as economic information but does not (and cannot in the current model) incorporate direct and future environmental data. For example, the NEMS model does not have a relationship between load and temperature, and thus cannot use such data as long-term temperature and atmospheric changes as an input. In addition, EIA’s System for Analysis of Global Energy Markets (SAGE) is an integrated set of regional models that provides a technology-rich basis for estimating regional energy supply and demand.94 As another example, the IEA Energy Technology Systems Anal...
